OBJECTIVEThe purpose of this study was to develop a model for assessing the 5-year risk of developing type 2 diabetes from a panel of 64 circulating candidate biomarkers.RESEARCH DESIGN AND METHODSSubjects were selected from the Inter99 cohort, a longitudinal population-based study of ∼6,600 Danes in a nested case-control design with the primary outcome of 5-year conversion to type 2 diabetes. Nondiabetic subjects, aged ≥39 years, with BMI ≥25 kg/m2 at baseline were selected. Baseline fasting serum samples from 160 individuals who developed type 2 diabetes and from 472 who did not were tested. An ultrasensitive immunoassay was used to measure of 58 candidate biomarkers in multiple diabetes-associated pathways, along with six routine clinical variables. Statistical learning methods and permutation testing were used to select the most informative biomarkers. Risk model performance was estimated using a validated bootstrap bias-correction procedure.RESULTSA model using six biomarkers (adiponectin, C-reactive protein, ferritin, interleukin-2 receptor A, glucose, and insulin) was developed for assessing an individual's 5-year risk of developing type 2 diabetes. This model has a bootstrap-estimated area under the curve of 0.76, which is greater than that for A1C, fasting plasma glucose, fasting serum insulin, BMI, sex-adjusted waist circumference, a model using fasting glucose and insulin, and a noninvasive clinical model.CONCLUSIONSA model incorporating six circulating biomarkers provides an objective and quantitative estimate of the 5-year risk of developing type 2 diabetes, performs better than single risk indicators and a noninvasive clinical model, and provides better stratification than fasting plasma glucose alone.

Pituitary adenylate cyclase-activating peptide (PACAP) and vasoactive intestinal peptide (VIP) activate two shared receptors, VPAC1 and VPAC2. Activation of VPAC1 has been implicated in elevating glucose output, whereas activation of VPAC2 may be involved in insulin secretion. A hypothesis that a VPAC2-selective agonist would enhance glucose disposal by stimulating insulin secretion without causing increased hepatic glucose production was tested using a novel selective agonist of VPAC2. This agonist, BAY 55-9837, was generated through site-directed mutagenesis based on sequence alignments of PACAP, VIP, and related analogs. The peptide bound to VPAC2 with a dissociation constant (K d ) of 0.65 nmol/l and displayed >100-fold selectivity over VPAC1. BAY 55-9837 stimulated glucose-dependent insulin secretion in isolated rat and human pancreatic islets, increased insulin synthesis in purified rat islets, and caused a dose-dependent increase in plasma insulin levels in fasted rats, with a half-maximal stimulatory concentration of 3 pmol/kg. Continuous intravenous or subcutaneous infusion of the peptide reduced the glucose area under the curve following an intraperitoneal glucose tolerance test. The peptide had effects on intestinal water retention and mean arterial blood pressure in rats, but only at much higher doses. BAY 55-9837 may be a useful therapy for the treatment of type 2 diabetes.

BACKGROUND:Myocardial infarction is diagnosed when biomarkers of cardiac necrosis exceed the 99th centile, although guidelines advocate even lower concentrations for early rule-out. We examined how many myocytes and how much myocardium these concentrations represent. We also examined if dietary troponin can confound the rule-out algorithm.

Pituitaryadenylate cyclase-activating peptide (PACAP) has a specific receptor PAC1 and shares two receptors VPAC1 and VPAC2 with vasoactive intestinal peptide (VIP). VPAC2 activation enhances glucose-induced insulin release while VPAC1 activation elevates glucose output. To generate a large pool of VPAC2 selective agonists for the treatment of type 2 diabetes, structure-activity relationship studies were performed on PACAP, VIP, and a VPAC2 selective VIP analog. Chemical modifications on this analog that prevent recombinant expression were sequentially removed to show that a recombinant peptide would retain VPAC2 selectivity. An efficient recombinant expression system was then developed to produce and screen hundreds of mutant peptides. The 11 mutations found on the VIP analog were systematically replaced with VIP or PACAP sequences. Three of these mutations, V19A, L27K, and N28K, were sufficient to provide most of the VPAC2 selectivity. C-terminal extension with the KRY sequence from PACAP38 led to potent VPAC2 agonists with improved selectivity (100 -1000-fold). Saturation mutagenesis at positions 19, 27, 29, and 30 of VIP and chargescanning mutagenesis of PACAP27 generated additional VPAC2 selective agonists. We have generated the first set of recombinant VPAC2 selective agonists described, which exhibit activity profiles that suggest therapeutic utility in the treatment of diabetes.Pituitary adenylate cyclase-activating polypeptide (PACAP), 1 originally isolated from ovine hypothalamus (1) by following pituitary adenylate cyclase activation, belongs to the secretin/glucagon/vasoactive intestinal peptide (VIP) family of peptides (2). These peptides are expressed as part of larger proteins that are processed by proteolysis followed by Cterminal amidation to generate the mature amidated peptides (Fig. 1). PACAP exists as a 38-residue form (PACAP38), and as a shorter form corresponding to the N-terminal 27 amino acids of PACAP38 (PACAP27). Both forms of PACAP bind to and activate the G-protein-coupled receptors PAC1, VPAC1, and VPAC2, whereas the related 28-mer peptide VIP only recognizes VPAC1 and VPAC2 (3). Activation of multiple receptors by PACAP or VIP has broad physiological effects on nervous, endocrine, cardiovascular, reproductive, muscular, and immune systems (4). Thus, clinical applications will require selective activation of a particular receptor to minimize potential side effects mediated by the other receptors. For example, we have previously demonstrated that VPAC2 activation induces glucose-dependent insulin secretion without the undesired side effects mediated by VPAC1 such as watery diarrhea (5). Therefore, to provide a potential therapy for type 2 diabetes, VPAC2 selectivity is an absolute requirement.We sought to identify key determinants of VPAC2 selectivity and generate a peptide with the minimum number of mutations. However, structure-function relationship studies on VIP and PACAP (6 -15) have been restricted by the number of peptides that can be tested due to limitations of peptide synth...

S everal predictive models are currently being used for risk stratification and clinical decision-making in cardiovascular medicine and primary healthcare.1,2 Most models are based on the traditional cardiovascular risk factors (TRF), that is, age, sex, blood pressure, total cholesterol, high-density lipoprotein cholesterol, and smoking status, and with the estimated 10-year risk of either cardiovascular mortality or event rate as outcome. However, it is evident that the traditional risk factors do not adequately reflect all cardiovascular risk because the majority of individuals who experience a first time cardiovascular event have adverse levels in <2 traditional risk factors and are misidentified as being at low risk. 3 Both the successes and shortcomings of the traditional risk factors have stimulated research into identifying additional biomarkers, that is, biological signals, which can be used to improve on current cardiovascular disease risk models, or are indicators of progressive subclinical disease and, as such, would have utility in predicting cardiovascular event risk, improve on traditional predictive models, and lead to more accurate treatment decisions. Blood-based biomarkers that can be easily integrated into patient management in the primary care setting are particularly desirable. Of the <60 different proteins screened to date, only 3, C-reactive protein (CRP), N-terminal prohormone of brain natriuretic peptide, and cardiac troponin I, have been shown, in combination only, to add incremental value to TRF-based predictive models of first-time CVD. 4 However, their clinical utility in preventive cardiology has not been clearly established. CRP, like other acute phase proteins, such as fibrinogen, is widely recognized to be a marker of a general inflammatory state that contributes to cardiovascular Background-Identification of individuals with high risk for first-ever myocardial infarction (MI) can be improved. The objectives of the study were to survey multiple protein biomarkers for association with the 10-year risk of incident MI and identify a clinically significant risk model that adds information to current common risk models. Methods and Results-We used an immunoassay platform that uses a sensitive, sample-efficient molecular counting technology to measure 51 proteins in samples from the fourth survey (1994) in the Tromsø Study, a longitudinal study of men and women in Tromsø, Norway. A case control design was used with 419 first-ever MI cases (169 females/250 males) and 398 controls (244 females/154 males). Of the proteins measured, 17 were predictors of MI when considered individually after adjustment for traditional risk factors either in men, women, or both. The 6 biomarkers adjusted for traditional risk factors that were selected in a multivariable model (odds ratios [OR] per standard deviation) using a stepwise procedure were apolipoprotein B/apolipoprotein A1 ratio (1.40), kallikrein (0.73), lipoprotein a (1.29), matrix metalloproteinase 9 (1.30), the interaction term IP-10/CXCL10×...

BACKGROUND Biomarkers for estimating reduced glucose tolerance, insulin sensitivity, or impaired insulin secretion would be clinically useful, since these physiologic measures are important in the pathogenesis of type 2 diabetes mellitus. METHODS We conducted a cross-sectional study in which 94 individuals, of whom 84 had 1 or more risk factors and 10 had no known risk factors for diabetes, underwent oral glucose tolerance testing. We measured 34 protein biomarkers associated with diabetes risk in 250-μL fasting serum samples. We applied multiple regression selection techniques to identify the most informative biomarkers and develop multivariate models to estimate glucose tolerance, insulin sensitivity, and insulin secretion. The ability of the glucose tolerance model to discriminate between diabetic individuals and those with impaired or normal glucose tolerance was evaluated by area under the ROC curve (AUC) analysis. RESULTS Of the at-risk participants, 25 (30%) were found to have impaired glucose tolerance, and 11 (13%) diabetes. Using molecular counting technology, we assessed multiple biomarkers with high accuracy in small volume samples. Multivariate biomarker models derived from fasting samples correlated strongly with 2-h postload glucose tolerance (R2 = 0.45, P < 0.0001), composite insulin sensitivity index (R2 = 0.91, P < 0.0001), and insulin secretion (R2 = 0.45, P < 0.0001). Additionally, the glucose tolerance model provided strong discrimination between diabetes vs impaired or normal glucose tolerance (AUC 0.89) and between diabetes and impaired glucose tolerance vs normal tolerance (AUC 0.78). CONCLUSIONS Biomarkers in fasting blood samples may be useful in estimating glucose tolerance, insulin sensitivity, and insulin secretion.

Complex diseases are caused by combinatorial genetic, environmental and lifestyle factors. The emergence of multibiomarker tests to define these diseases and to identify the early, presymptomatic stages offers several advantages to the conventional use of single marker tests. The development of multibiomarker protein-based tests remains constrained by technological and operational limitations in assaying hundreds to thousands of proteins in thousands of samples. In order to develop a multibiomarker test that stratifies risk for Type 2 diabetes, we took a candidate-driven immunoassay approach utilizing a microfluidics platform to analyze 89 candidate proteins in thousands of samples, which allowed us to move from discovery to a commercial test in 2 years. Future multibiomarker test development will be enhanced by advancements in the number of proteins that can be analyzed, analytical sensitivity and throughput, and sample volume requirements, all of which depend on the further advancement of microfluidics, detection technologies and affinity-based reagents.

BackgroundCoffee consumption has been associated with reduced risk of developing type 2 diabetes mellitus (T2DM) however, the mechanism for this association has yet to be elucidated. Non-alcoholic fatty liver disease (NAFLD) characterizes and predicts T2DM yet the relationship of coffee with this disorder remains unclear. Our aim was to investigate the associations of coffee with markers of liver injury in 1005 multi-ethnic, non-diabetic adults in the Insulin Resistance Atherosclerosis Study.MethodsDietary intake was assessed using a validated 114-item food frequency questionnaire. Alanine aminotransferase (ALT), aspartate aminotransferase (AST) and fetuin-A were determined in fasting blood samples and the validated NAFLD liver fat score was calculated. Multivariate linear regression assessed the contribution of coffee to variation in markers of liver injury.ResultsCaffeinated coffee showed significant inverse associations with ALT (β = −0.08, p = 0.0111), AST (β = −0.05, p = 0.0155) and NAFLD liver fat score (β = −0.05, p = 0.0293) but not with fetuin-A (β = 0.04, p = 0.17). When the highest alcohol consumers were excluded, these associations remained (ALT β = −0.11, p = 0.0037; AST β = −0.05, p = 0.0330; NAFLD liver fat score β = −0.06, p = 0.0298). With additional adjustment for insulin sensitivity, the relationship with ALT remained significant (ALT β = −0.08, p = 0.0400; AST β = −0.03, p = 0.20; NAFLD liver fat score β = −0.03, p = 0.27). There were no significant associations of decaffeinated coffee with liver markers.ConclusionsThese analyses indicate a beneficial impact of caffeinated coffee on liver morphology and/or function, and suggest that this relationship may mediate the well-established inverse association of coffee with risk of T2DM.Electronic supplementary materialThe online version of this article (doi:10.1186/s12876-015-0321-3) contains supplementary material, which is available to authorized users.